Client Secrets

Create client secret

client.Realtime.ClientSecrets.New(ctx, body) (*ClientSecretNewResponse, error)

post /realtime/client_secrets

Create client secret

Parameters

body ClientSecretNewParams
- ExpiresAfter param.Field[ClientSecretNewParamsExpiresAfter]
  
  Configuration for the client secret expiration. Expiration refers to the time after which a client secret will no longer be valid for creating sessions. The session itself may continue after that time once started. A secret can be used to create multiple sessions until it expires.
  - Anchor string
    
    The anchor point for the client secret expiration, meaning that seconds will be added to the created_at time of the client secret to produce an expiration timestamp. Only created_at is currently supported.
    - const ClientSecretNewParamsExpiresAfterAnchorCreatedAt ClientSecretNewParamsExpiresAfterAnchor = "created_at"
  - Seconds int64
    
    The number of seconds from the anchor point to the expiration. Select a value between 10 and 7200 (2 hours). This default to 600 seconds (10 minutes) if not specified.
- Session param.Field[ClientSecretNewParamsSessionUnion]
  
  Session configuration to use for the client secret. Choose either a realtime session or a transcription session.
  - type RealtimeSessionCreateRequest struct{…}
    
    Realtime session object configuration.
    - Type Realtime
      
      The type of session to create. Always realtime for the Realtime API.
      - const RealtimeRealtime Realtime = "realtime"
    - Audio RealtimeAudioConfig
      
      Configuration for input and output audio.
      - Input RealtimeAudioConfigInput
        
        Format RealtimeAudioFormatsUnion
        
        The format of the input audio.
        
        type RealtimeAudioFormatsAudioPCM struct{…}
        
        The PCM audio format. Only a 24kHz sample rate is supported.
        
        Rate int64
        
        The sample rate of the audio. Always 24000.
        
        const RealtimeAudioFormatsAudioPCMRate24000 RealtimeAudioFormatsAudioPCMRate = 24000
        
        Type string
        
        The audio format. Always audio/pcm.
        
        const RealtimeAudioFormatsAudioPCMTypeAudioPCM RealtimeAudioFormatsAudioPCMType = "audio/pcm"
        
        type RealtimeAudioFormatsAudioPCMU struct{…}
        
        The G.711 μ-law format.
        
        Type string
        
        The audio format. Always audio/pcmu.
        
        const RealtimeAudioFormatsAudioPCMUTypeAudioPCMU RealtimeAudioFormatsAudioPCMUType = "audio/pcmu"
        
        type RealtimeAudioFormatsAudioPCMA struct{…}
        
        The G.711 A-law format.
        
        Type string
        
        The audio format. Always audio/pcma.
        
        const RealtimeAudioFormatsAudioPCMATypeAudioPCMA RealtimeAudioFormatsAudioPCMAType = "audio/pcma"
        
        NoiseReduction RealtimeAudioConfigInputNoiseReduction
        
        Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.
        
        Type NoiseReductionType
        
        Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.
        
        const NoiseReductionTypeNearField NoiseReductionType = "near_field"
        
        const NoiseReductionTypeFarField NoiseReductionType = "far_field"
        
        Transcription AudioTranscription
        
        Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.
        
        Delay AudioTranscriptionDelay
        
        Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.
        
        const AudioTranscriptionDelayMinimal AudioTranscriptionDelay = "minimal"
        
        const AudioTranscriptionDelayLow AudioTranscriptionDelay = "low"
        
        const AudioTranscriptionDelayMedium AudioTranscriptionDelay = "medium"
        
        const AudioTranscriptionDelayHigh AudioTranscriptionDelay = "high"
        
        const AudioTranscriptionDelayXhigh AudioTranscriptionDelay = "xhigh"
        
        Language string
        
        The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.
        
        Model AudioTranscriptionModel
        
        The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.
        
        string
        
        type AudioTranscriptionModel string
        
        The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.
        
        const AudioTranscriptionModelWhisper1 AudioTranscriptionModel = "whisper-1"
        
        const AudioTranscriptionModelGPT4oMiniTranscribe AudioTranscriptionModel = "gpt-4o-mini-transcribe"
        
        const AudioTranscriptionModelGPT4oMiniTranscribe2025_12_15 AudioTranscriptionModel = "gpt-4o-mini-transcribe-2025-12-15"
        
        const AudioTranscriptionModelGPT4oTranscribe AudioTranscriptionModel = "gpt-4o-transcribe"
        
        const AudioTranscriptionModelGPT4oTranscribeDiarize AudioTranscriptionModel = "gpt-4o-transcribe-diarize"
        
        const AudioTranscriptionModelGPTRealtimeWhisper AudioTranscriptionModel = "gpt-realtime-whisper"
        
        Prompt string
        
        An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.
        
        TurnDetection RealtimeAudioInputTurnDetectionUnion
        
        Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.
        
        Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.
        
        Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.
        
        For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.
        
        RealtimeAudioInputTurnDetectionServerVad
        
        Type ServerVad
        
        Type of turn detection, server_vad to turn on simple Server VAD.
        
        const ServerVadServerVad ServerVad = "server_vad"
        
        CreateResponse bool
        
        Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.
        
        If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.
        
        IdleTimeoutMs int64
        
        Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.
        
        The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.
        
        An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.
        
        InterruptResponse bool
        
        Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.
        
        If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.
        
        PrefixPaddingMs int64
        
        Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.
        
        SilenceDurationMs int64
        
        Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.
        
        Threshold float64
        
        Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.
        
        RealtimeAudioInputTurnDetectionSemanticVad
        
        Type SemanticVad
        
        Type of turn detection, semantic_vad to turn on Semantic VAD.
        
        const SemanticVadSemanticVad SemanticVad = "semantic_vad"
        
        CreateResponse bool
        
        Whether or not to automatically generate a response when a VAD stop event occurs.
        
        Eagerness string
        
        Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.
        
        const RealtimeAudioInputTurnDetectionSemanticVadEagernessLow RealtimeAudioInputTurnDetectionSemanticVadEagerness = "low"
        
        const RealtimeAudioInputTurnDetectionSemanticVadEagernessMedium RealtimeAudioInputTurnDetectionSemanticVadEagerness = "medium"
        
        const RealtimeAudioInputTurnDetectionSemanticVadEagernessHigh RealtimeAudioInputTurnDetectionSemanticVadEagerness = "high"
        
        const RealtimeAudioInputTurnDetectionSemanticVadEagernessAuto RealtimeAudioInputTurnDetectionSemanticVadEagerness = "auto"
        
        InterruptResponse bool
        
        Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.
      - Output RealtimeAudioConfigOutput
        
        Format RealtimeAudioFormatsUnion
        
        The format of the output audio.
        
        Speed float64
        
        The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.
        
        This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.
        
        Voice RealtimeAudioConfigOutputVoiceUnion
        
        The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.
        
        string
        
        string
        
        const RealtimeAudioConfigOutputVoiceString2Alloy RealtimeAudioConfigOutputVoiceString2 = "alloy"
        
        const RealtimeAudioConfigOutputVoiceString2Ash RealtimeAudioConfigOutputVoiceString2 = "ash"
        
        const RealtimeAudioConfigOutputVoiceString2Ballad RealtimeAudioConfigOutputVoiceString2 = "ballad"
        
        const RealtimeAudioConfigOutputVoiceString2Coral RealtimeAudioConfigOutputVoiceString2 = "coral"
        
        const RealtimeAudioConfigOutputVoiceString2Echo RealtimeAudioConfigOutputVoiceString2 = "echo"
        
        const RealtimeAudioConfigOutputVoiceString2Sage RealtimeAudioConfigOutputVoiceString2 = "sage"
        
        const RealtimeAudioConfigOutputVoiceString2Shimmer RealtimeAudioConfigOutputVoiceString2 = "shimmer"
        
        const RealtimeAudioConfigOutputVoiceString2Verse RealtimeAudioConfigOutputVoiceString2 = "verse"
        
        const RealtimeAudioConfigOutputVoiceString2Marin RealtimeAudioConfigOutputVoiceString2 = "marin"
        
        const RealtimeAudioConfigOutputVoiceString2Cedar RealtimeAudioConfigOutputVoiceString2 = "cedar"
        
        RealtimeAudioConfigOutputVoiceID
        
        ID string
        
        The custom voice ID, e.g. voice_1234.
    - Include []string
      
      Additional fields to include in server outputs.
      
      item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.
      - const RealtimeSessionCreateRequestIncludeItemInputAudioTranscriptionLogprobs RealtimeSessionCreateRequestInclude = "item.input_audio_transcription.logprobs"
    - Instructions string
      
      The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.
      
      Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.
    - MaxOutputTokens RealtimeSessionCreateRequestMaxOutputTokensUnion
      
      Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.
      - int64
      - Inf
        
        const InfInf Inf = "inf"
    - Model RealtimeSessionCreateRequestModel
      
      The Realtime model used for this session.
      - string
      - RealtimeSessionCreateRequestModel
        
        const RealtimeSessionCreateRequestModelGPTRealtime RealtimeSessionCreateRequestModel = "gpt-realtime"
        
        const RealtimeSessionCreateRequestModelGPTRealtime1_5 RealtimeSessionCreateRequestModel = "gpt-realtime-1.5"
        
        const RealtimeSessionCreateRequestModelGPTRealtime2 RealtimeSessionCreateRequestModel = "gpt-realtime-2"
        
        const RealtimeSessionCreateRequestModelGPTRealtime2_1 RealtimeSessionCreateRequestModel = "gpt-realtime-2.1"
        
        const RealtimeSessionCreateRequestModelGPTRealtime2_1Mini RealtimeSessionCreateRequestModel = "gpt-realtime-2.1-mini"
        
        const RealtimeSessionCreateRequestModelGPTRealtime2025_08_28 RealtimeSessionCreateRequestModel = "gpt-realtime-2025-08-28"
        
        const RealtimeSessionCreateRequestModelGPT4oRealtimePreview RealtimeSessionCreateRequestModel = "gpt-4o-realtime-preview"
        
        const RealtimeSessionCreateRequestModelGPT4oRealtimePreview2024_10_01 RealtimeSessionCreateRequestModel = "gpt-4o-realtime-preview-2024-10-01"
        
        const RealtimeSessionCreateRequestModelGPT4oRealtimePreview2024_12_17 RealtimeSessionCreateRequestModel = "gpt-4o-realtime-preview-2024-12-17"
        
        const RealtimeSessionCreateRequestModelGPT4oRealtimePreview2025_06_03 RealtimeSessionCreateRequestModel = "gpt-4o-realtime-preview-2025-06-03"
        
        const RealtimeSessionCreateRequestModelGPT4oMiniRealtimePreview RealtimeSessionCreateRequestModel = "gpt-4o-mini-realtime-preview"
        
        const RealtimeSessionCreateRequestModelGPT4oMiniRealtimePreview2024_12_17 RealtimeSessionCreateRequestModel = "gpt-4o-mini-realtime-preview-2024-12-17"
        
        const RealtimeSessionCreateRequestModelGPTRealtimeMini RealtimeSessionCreateRequestModel = "gpt-realtime-mini"
        
        const RealtimeSessionCreateRequestModelGPTRealtimeMini2025_10_06 RealtimeSessionCreateRequestModel = "gpt-realtime-mini-2025-10-06"
        
        const RealtimeSessionCreateRequestModelGPTRealtimeMini2025_12_15 RealtimeSessionCreateRequestModel = "gpt-realtime-mini-2025-12-15"
        
        const RealtimeSessionCreateRequestModelGPTAudio1_5 RealtimeSessionCreateRequestModel = "gpt-audio-1.5"
        
        const RealtimeSessionCreateRequestModelGPTAudioMini RealtimeSessionCreateRequestModel = "gpt-audio-mini"
        
        const RealtimeSessionCreateRequestModelGPTAudioMini2025_10_06 RealtimeSessionCreateRequestModel = "gpt-audio-mini-2025-10-06"
        
        const RealtimeSessionCreateRequestModelGPTAudioMini2025_12_15 RealtimeSessionCreateRequestModel = "gpt-audio-mini-2025-12-15"
    - OutputModalities []string
      
      The set of modalities the model can respond with. It defaults to ["audio"], indicating that the model will respond with audio plus a transcript. ["text"] can be used to make the model respond with text only. It is not possible to request both text and audio at the same time.
      - const RealtimeSessionCreateRequestOutputModalityText RealtimeSessionCreateRequestOutputModality = "text"
      - const RealtimeSessionCreateRequestOutputModalityAudio RealtimeSessionCreateRequestOutputModality = "audio"
    - ParallelToolCalls bool
      
      Whether the model may call multiple tools in parallel. Only supported by reasoning Realtime models such as gpt-realtime-2.
    - Prompt ResponsePrompt
      
      Reference to a prompt template and its variables. Learn more.
      - ID string
        
        The unique identifier of the prompt template to use.
      - Variables map[string, ResponsePromptVariableUnion]
        
        Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.
        
        string
        
        type ResponseInputText struct{…}
        
        A text input to the model.
        
        Text string
        
        The text input to the model.
        
        Type InputText
        
        The type of the input item. Always input_text.
        
        const InputTextInputText InputText = "input_text"
        
        PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint
        
        Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
        
        Mode Explicit
        
        The breakpoint mode. Always explicit.
        
        const ExplicitExplicit Explicit = "explicit"
        
        type ResponseInputImage struct{…}
        
        An image input to the model. Learn about image inputs.
        
        Detail ResponseInputImageDetail
        
        The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.
        
        const ResponseInputImageDetailLow ResponseInputImageDetail = "low"
        
        const ResponseInputImageDetailHigh ResponseInputImageDetail = "high"
        
        const ResponseInputImageDetailAuto ResponseInputImageDetail = "auto"
        
        const ResponseInputImageDetailOriginal ResponseInputImageDetail = "original"
        
        Type InputImage
        
        The type of the input item. Always input_image.
        
        const InputImageInputImage InputImage = "input_image"
        
        FileID string
        
        The ID of the file to be sent to the model.
        
        ImageURL string
        
        The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.
        
        PromptCacheBreakpoint ResponseInputImagePromptCacheBreakpoint
        
        Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
        
        Mode Explicit
        
        The breakpoint mode. Always explicit.
        
        const ExplicitExplicit Explicit = "explicit"
        
        type ResponseInputFile struct{…}
        
        A file input to the model.
        
        Type InputFile
        
        The type of the input item. Always input_file.
        
        const InputFileInputFile InputFile = "input_file"
        
        Detail ResponseInputFileDetail
        
        The detail level of the file to be sent to the model. Use auto to let the system select the detail level; for GPT-5.6 and later models, auto uses high-quality rendering, which may increase input token usage. Use low for lower-cost rendering, or high to render the file at higher quality. Defaults to auto.
        
        const ResponseInputFileDetailAuto ResponseInputFileDetail = "auto"
        
        const ResponseInputFileDetailLow ResponseInputFileDetail = "low"
        
        const ResponseInputFileDetailHigh ResponseInputFileDetail = "high"
        
        FileData string
        
        The content of the file to be sent to the model.
        
        FileID string
        
        The ID of the file to be sent to the model.
        
        FileURL string
        
        The URL of the file to be sent to the model.
        
        Filename string
        
        The name of the file to be sent to the model.
        
        PromptCacheBreakpoint ResponseInputFilePromptCacheBreakpoint
        
        Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
        
        Mode Explicit
        
        The breakpoint mode. Always explicit.
        
        const ExplicitExplicit Explicit = "explicit"
      - Version string
        
        Optional version of the prompt template.
    - Reasoning RealtimeReasoning
      
      Configuration for reasoning-capable Realtime models such as gpt-realtime-2.
      - Effort RealtimeReasoningEffort
        
        Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.
        
        const RealtimeReasoningEffortMinimal RealtimeReasoningEffort = "minimal"
        
        const RealtimeReasoningEffortLow RealtimeReasoningEffort = "low"
        
        const RealtimeReasoningEffortMedium RealtimeReasoningEffort = "medium"
        
        const RealtimeReasoningEffortHigh RealtimeReasoningEffort = "high"
        
        const RealtimeReasoningEffortXhigh RealtimeReasoningEffort = "xhigh"
    - ToolChoice RealtimeToolChoiceConfigUnion
      
      How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.
      - type ToolChoiceOptions string
        
        Controls which (if any) tool is called by the model.
        
        none means the model will not call any tool and instead generates a message.
        
        auto means the model can pick between generating a message or calling one or more tools.
        
        required means the model must call one or more tools.
        
        const ToolChoiceOptionsNone ToolChoiceOptions = "none"
        
        const ToolChoiceOptionsAuto ToolChoiceOptions = "auto"
        
        const ToolChoiceOptionsRequired ToolChoiceOptions = "required"
      - type ToolChoiceFunction struct{…}
        
        Use this option to force the model to call a specific function.
        
        Name string
        
        The name of the function to call.
        
        Type Function
        
        For function calling, the type is always function.
        
        const FunctionFunction Function = "function"
      - type ToolChoiceMcp struct{…}
        
        Use this option to force the model to call a specific tool on a remote MCP server.
        
        ServerLabel string
        
        The label of the MCP server to use.
        
        Type Mcp
        
        For MCP tools, the type is always mcp.
        
        const McpMcp Mcp = "mcp"
        
        Name string
        
        The name of the tool to call on the server.
    - Tools RealtimeToolsConfig
      
      Tools available to the model.
      - type RealtimeFunctionTool struct{…}
        
        Description string
        
        The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).
        
        Name string
        
        The name of the function.
        
        Parameters any
        
        Parameters of the function in JSON Schema.
        
        Type RealtimeFunctionToolType
        
        The type of the tool, i.e. function.
        
        const RealtimeFunctionToolTypeFunction RealtimeFunctionToolType = "function"
      - RealtimeToolsConfigUnionMcp
        
        ServerLabel string
        
        A label for this MCP server, used to identify it in tool calls.
        
        Type Mcp
        
        The type of the MCP tool. Always mcp.
        
        const McpMcp Mcp = "mcp"
        
        AllowedCallers []string
        
        The tool invocation context(s).
        
        const RealtimeToolsConfigUnionMcpAllowedCallerDirect RealtimeToolsConfigUnionMcpAllowedCaller = "direct"
        
        const RealtimeToolsConfigUnionMcpAllowedCallerProgrammatic RealtimeToolsConfigUnionMcpAllowedCaller = "programmatic"
        
        AllowedTools RealtimeToolsConfigUnionMcpAllowedTools
        
        List of allowed tool names or a filter object.
        
        []string
        
        RealtimeToolsConfigUnionMcpAllowedToolsMcpToolFilter
        
        ReadOnly bool
        
        Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.
        
        ToolNames []string
        
        List of allowed tool names.
        
        Authorization string
        
        An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.
        
        ConnectorID string
        
        Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.
        
        Currently supported connector_id values are:
        
        Dropbox: connector_dropbox
        
        Gmail: connector_gmail
        
        Google Calendar: connector_googlecalendar
        
        Google Drive: connector_googledrive
        
        Microsoft Teams: connector_microsoftteams
        
        Outlook Calendar: connector_outlookcalendar
        
        Outlook Email: connector_outlookemail
        
        SharePoint: connector_sharepoint
        
        const RealtimeToolsConfigUnionMcpConnectorIDConnectorDropbox RealtimeToolsConfigUnionMcpConnectorID = "connector_dropbox"
        
        const RealtimeToolsConfigUnionMcpConnectorIDConnectorGmail RealtimeToolsConfigUnionMcpConnectorID = "connector_gmail"
        
        const RealtimeToolsConfigUnionMcpConnectorIDConnectorGooglecalendar RealtimeToolsConfigUnionMcpConnectorID = "connector_googlecalendar"
        
        const RealtimeToolsConfigUnionMcpConnectorIDConnectorGoogledrive RealtimeToolsConfigUnionMcpConnectorID = "connector_googledrive"
        
        const RealtimeToolsConfigUnionMcpConnectorIDConnectorMicrosoftteams RealtimeToolsConfigUnionMcpConnectorID = "connector_microsoftteams"
        
        const RealtimeToolsConfigUnionMcpConnectorIDConnectorOutlookcalendar RealtimeToolsConfigUnionMcpConnectorID = "connector_outlookcalendar"
        
        const RealtimeToolsConfigUnionMcpConnectorIDConnectorOutlookemail RealtimeToolsConfigUnionMcpConnectorID = "connector_outlookemail"
        
        const RealtimeToolsConfigUnionMcpConnectorIDConnectorSharepoint RealtimeToolsConfigUnionMcpConnectorID = "connector_sharepoint"
        
        DeferLoading bool
        
        Whether this MCP tool is deferred and discovered via tool search.
        
        Headers map[string, string]
        
        Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.
        
        RequireApproval RealtimeToolsConfigUnionMcpRequireApproval
        
        Specify which of the MCP server's tools require approval.
        
        RealtimeToolsConfigUnionMcpRequireApprovalMcpToolApprovalFilter
        
        Always RealtimeToolsConfigUnionMcpRequireApprovalMcpToolApprovalFilterAlways
        
        A filter object to specify which tools are allowed.
        
        ReadOnly bool
        
        Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.
        
        ToolNames []string
        
        List of allowed tool names.
        
        Never RealtimeToolsConfigUnionMcpRequireApprovalMcpToolApprovalFilterNever
        
        A filter object to specify which tools are allowed.
        
        ReadOnly bool
        
        Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.
        
        ToolNames []string
        
        List of allowed tool names.
        
        string
        
        const RealtimeToolsConfigUnionMcpRequireApprovalMcpToolApprovalSettingAlways RealtimeToolsConfigUnionMcpRequireApprovalMcpToolApprovalSetting = "always"
        
        const RealtimeToolsConfigUnionMcpRequireApprovalMcpToolApprovalSettingNever RealtimeToolsConfigUnionMcpRequireApprovalMcpToolApprovalSetting = "never"
        
        ServerDescription string
        
        Optional description of the MCP server, used to provide more context.
        
        ServerURL string
        
        The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.
        
        TunnelID string
        
        The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.
    - Tracing RealtimeTracingConfigUnion
      
      Realtime API can write session traces to the Traces Dashboard. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.
      
      auto will create a trace for the session with default values for the workflow name, group id, and metadata.
      - Auto
        
        const AutoAuto Auto = "auto"
      - RealtimeTracingConfigTracingConfiguration
        
        GroupID string
        
        The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.
        
        Metadata any
        
        The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.
        
        WorkflowName string
        
        The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.
    - Truncation RealtimeTruncationUnion
      
      When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.
      
      Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.
      
      Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.
      
      Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.
      - type RealtimeTruncationRealtimeTruncationStrategy string
        
        The truncation strategy to use for the session. auto is the default truncation strategy. disabled will disable truncation and emit errors when the conversation exceeds the input token limit.
        
        const RealtimeTruncationRealtimeTruncationStrategyAuto RealtimeTruncationRealtimeTruncationStrategy = "auto"
        
        const RealtimeTruncationRealtimeTruncationStrategyDisabled RealtimeTruncationRealtimeTruncationStrategy = "disabled"
      - type RealtimeTruncationRetentionRatio struct{…}
        
        Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.
        
        RetentionRatio float64
        
        Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.
        
        Type RetentionRatio
        
        Use retention ratio truncation.
        
        const RetentionRatioRetentionRatio RetentionRatio = "retention_ratio"
        
        TokenLimits RealtimeTruncationRetentionRatioTokenLimits
        
        Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.
        
        PostInstructions int64
        
        Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.
  - type RealtimeTranscriptionSessionCreateRequest struct{…}
    
    Realtime transcription session object configuration.
    - Type Transcription
      
      The type of session to create. Always transcription for transcription sessions.
      - const TranscriptionTranscription Transcription = "transcription"
    - Audio RealtimeTranscriptionSessionAudio
      
      Configuration for input and output audio.
      - Input RealtimeTranscriptionSessionAudioInput
        
        Format RealtimeAudioFormatsUnion
        
        The PCM audio format. Only a 24kHz sample rate is supported.
        
        NoiseReduction RealtimeTranscriptionSessionAudioInputNoiseReduction
        
        Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.
        
        Type NoiseReductionType
        
        Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.
        
        Transcription AudioTranscription
        
        Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.
        
        TurnDetection RealtimeTranscriptionSessionAudioInputTurnDetectionUnion
        
        Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.
        
        Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.
        
        Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.
        
        For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.
        
        RealtimeTranscriptionSessionAudioInputTurnDetectionServerVad
        
        Type ServerVad
        
        Type of turn detection, server_vad to turn on simple Server VAD.
        
        const ServerVadServerVad ServerVad = "server_vad"
        
        CreateResponse bool
        
        Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.
        
        If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.
        
        IdleTimeoutMs int64
        
        Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.
        
        The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.
        
        An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.
        
        InterruptResponse bool
        
        Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.
        
        If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.
        
        PrefixPaddingMs int64
        
        Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.
        
        SilenceDurationMs int64
        
        Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.
        
        Threshold float64
        
        Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.
        
        RealtimeTranscriptionSessionAudioInputTurnDetectionSemanticVad
        
        Type SemanticVad
        
        Type of turn detection, semantic_vad to turn on Semantic VAD.
        
        const SemanticVadSemanticVad SemanticVad = "semantic_vad"
        
        CreateResponse bool
        
        Whether or not to automatically generate a response when a VAD stop event occurs.
        
        Eagerness string
        
        Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.
        
        const RealtimeTranscriptionSessionAudioInputTurnDetectionSemanticVadEagernessLow RealtimeTranscriptionSessionAudioInputTurnDetectionSemanticVadEagerness = "low"
        
        const RealtimeTranscriptionSessionAudioInputTurnDetectionSemanticVadEagernessMedium RealtimeTranscriptionSessionAudioInputTurnDetectionSemanticVadEagerness = "medium"
        
        const RealtimeTranscriptionSessionAudioInputTurnDetectionSemanticVadEagernessHigh RealtimeTranscriptionSessionAudioInputTurnDetectionSemanticVadEagerness = "high"
        
        const RealtimeTranscriptionSessionAudioInputTurnDetectionSemanticVadEagernessAuto RealtimeTranscriptionSessionAudioInputTurnDetectionSemanticVadEagerness = "auto"
        
        InterruptResponse bool
        
        Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.
    - Include []string
      
      Additional fields to include in server outputs.
      
      item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.
      - const RealtimeTranscriptionSessionCreateRequestIncludeItemInputAudioTranscriptionLogprobs RealtimeTranscriptionSessionCreateRequestInclude = "item.input_audio_transcription.logprobs"

Returns

type ClientSecretNewResponse struct{…}

Response from creating a session and client secret for the Realtime API.
- ExpiresAt int64
  
  Expiration timestamp for the client secret, in seconds since epoch.
- Session ClientSecretNewResponseSessionUnion
  
  The session configuration for either a realtime or transcription session.
  - type RealtimeSessionCreateResponse struct{…}
    
    A Realtime session configuration object.
    - ID string
      
      Unique identifier for the session that looks like sess_1234567890abcdef.
    - Object RealtimeSession
      
      The object type. Always realtime.session.
      - const RealtimeSessionRealtimeSession RealtimeSession = "realtime.session"
    - Type Realtime
      
      The type of session to create. Always realtime for the Realtime API.
      - const RealtimeRealtime Realtime = "realtime"
    - Audio RealtimeSessionCreateResponseAudio
      
      Configuration for input and output audio.
      - Input RealtimeSessionCreateResponseAudioInput
        
        Format RealtimeAudioFormatsUnion
        
        The format of the input audio.
        
        type RealtimeAudioFormatsAudioPCM struct{…}
        
        The PCM audio format. Only a 24kHz sample rate is supported.
        
        Rate int64
        
        The sample rate of the audio. Always 24000.
        
        const RealtimeAudioFormatsAudioPCMRate24000 RealtimeAudioFormatsAudioPCMRate = 24000
        
        Type string
        
        The audio format. Always audio/pcm.
        
        const RealtimeAudioFormatsAudioPCMTypeAudioPCM RealtimeAudioFormatsAudioPCMType = "audio/pcm"
        
        type RealtimeAudioFormatsAudioPCMU struct{…}
        
        The G.711 μ-law format.
        
        Type string
        
        The audio format. Always audio/pcmu.
        
        const RealtimeAudioFormatsAudioPCMUTypeAudioPCMU RealtimeAudioFormatsAudioPCMUType = "audio/pcmu"
        
        type RealtimeAudioFormatsAudioPCMA struct{…}
        
        The G.711 A-law format.
        
        Type string
        
        The audio format. Always audio/pcma.
        
        const RealtimeAudioFormatsAudioPCMATypeAudioPCMA RealtimeAudioFormatsAudioPCMAType = "audio/pcma"
        
        NoiseReduction RealtimeSessionCreateResponseAudioInputNoiseReduction
        
        Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.
        
        Type NoiseReductionType
        
        Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.
        
        const NoiseReductionTypeNearField NoiseReductionType = "near_field"
        
        const NoiseReductionTypeFarField NoiseReductionType = "far_field"
        
        Transcription AudioTranscription
        
        Delay AudioTranscriptionDelay
        
        Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.
        
        const AudioTranscriptionDelayMinimal AudioTranscriptionDelay = "minimal"
        
        const AudioTranscriptionDelayLow AudioTranscriptionDelay = "low"
        
        const AudioTranscriptionDelayMedium AudioTranscriptionDelay = "medium"
        
        const AudioTranscriptionDelayHigh AudioTranscriptionDelay = "high"
        
        const AudioTranscriptionDelayXhigh AudioTranscriptionDelay = "xhigh"
        
        Language string
        
        The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.
        
        Model AudioTranscriptionModel
        
        The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.
        
        string
        
        type AudioTranscriptionModel string
        
        The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.
        
        const AudioTranscriptionModelWhisper1 AudioTranscriptionModel = "whisper-1"
        
        const AudioTranscriptionModelGPT4oMiniTranscribe AudioTranscriptionModel = "gpt-4o-mini-transcribe"
        
        const AudioTranscriptionModelGPT4oMiniTranscribe2025_12_15 AudioTranscriptionModel = "gpt-4o-mini-transcribe-2025-12-15"
        
        const AudioTranscriptionModelGPT4oTranscribe AudioTranscriptionModel = "gpt-4o-transcribe"
        
        const AudioTranscriptionModelGPT4oTranscribeDiarize AudioTranscriptionModel = "gpt-4o-transcribe-diarize"
        
        const AudioTranscriptionModelGPTRealtimeWhisper AudioTranscriptionModel = "gpt-realtime-whisper"
        
        Prompt string
        
        An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.
        
        TurnDetection RealtimeSessionCreateResponseAudioInputTurnDetectionUnion
        
        Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.
        
        Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.
        
        Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.
        
        For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.
        
        type RealtimeSessionCreateResponseAudioInputTurnDetectionServerVad struct{…}
        
        Server-side voice activity detection (VAD) which flips on when user speech is detected and off after a period of silence.
        
        Type ServerVad
        
        Type of turn detection, server_vad to turn on simple Server VAD.
        
        const ServerVadServerVad ServerVad = "server_vad"
        
        CreateResponse bool
        
        Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.
        
        If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.
        
        IdleTimeoutMs int64
        
        Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.
        
        The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.
        
        An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.
        
        InterruptResponse bool
        
        Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.
        
        If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.
        
        PrefixPaddingMs int64
        
        Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.
        
        SilenceDurationMs int64
        
        Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.
        
        Threshold float64
        
        Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.
        
        type RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVad struct{…}
        
        Server-side semantic turn detection which uses a model to determine when the user has finished speaking.
        
        Type SemanticVad
        
        Type of turn detection, semantic_vad to turn on Semantic VAD.
        
        const SemanticVadSemanticVad SemanticVad = "semantic_vad"
        
        CreateResponse bool
        
        Whether or not to automatically generate a response when a VAD stop event occurs.
        
        Eagerness string
        
        Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.
        
        const RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagernessLow RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagerness = "low"
        
        const RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagernessMedium RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagerness = "medium"
        
        const RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagernessHigh RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagerness = "high"
        
        const RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagernessAuto RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagerness = "auto"
        
        InterruptResponse bool
        
        Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.
      - Output RealtimeSessionCreateResponseAudioOutput
        
        Format RealtimeAudioFormatsUnion
        
        The format of the output audio.
        
        Speed float64
        
        The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.
        
        This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.
        
        Voice string
        
        The voice the model uses to respond. Voice cannot be changed during the session once the model has responded with audio at least once. Current voice options are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. We recommend marin and cedar for best quality.
        
        string
        
        string
        
        const RealtimeSessionCreateResponseAudioOutputVoiceAlloy RealtimeSessionCreateResponseAudioOutputVoice = "alloy"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceAsh RealtimeSessionCreateResponseAudioOutputVoice = "ash"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceBallad RealtimeSessionCreateResponseAudioOutputVoice = "ballad"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceCoral RealtimeSessionCreateResponseAudioOutputVoice = "coral"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceEcho RealtimeSessionCreateResponseAudioOutputVoice = "echo"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceSage RealtimeSessionCreateResponseAudioOutputVoice = "sage"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceShimmer RealtimeSessionCreateResponseAudioOutputVoice = "shimmer"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceVerse RealtimeSessionCreateResponseAudioOutputVoice = "verse"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceMarin RealtimeSessionCreateResponseAudioOutputVoice = "marin"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceCedar RealtimeSessionCreateResponseAudioOutputVoice = "cedar"
    - ExpiresAt int64
      
      Expiration timestamp for the session, in seconds since epoch.
    - Include []string
      
      Additional fields to include in server outputs.
      
      item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.
      - const RealtimeSessionCreateResponseIncludeItemInputAudioTranscriptionLogprobs RealtimeSessionCreateResponseInclude = "item.input_audio_transcription.logprobs"
    - Instructions string
      
      The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.
      
      Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.
    - MaxOutputTokens RealtimeSessionCreateResponseMaxOutputTokensUnion
      
      Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.
      - int64
      - type Inf string
        
        const InfInf Inf = "inf"
    - Model RealtimeSessionCreateResponseModel
      
      The Realtime model used for this session.
      - string
      - type RealtimeSessionCreateResponseModel string
        
        The Realtime model used for this session.
        
        const RealtimeSessionCreateResponseModelGPTRealtime RealtimeSessionCreateResponseModel = "gpt-realtime"
        
        const RealtimeSessionCreateResponseModelGPTRealtime1_5 RealtimeSessionCreateResponseModel = "gpt-realtime-1.5"
        
        const RealtimeSessionCreateResponseModelGPTRealtime2 RealtimeSessionCreateResponseModel = "gpt-realtime-2"
        
        const RealtimeSessionCreateResponseModelGPTRealtime2_1 RealtimeSessionCreateResponseModel = "gpt-realtime-2.1"
        
        const RealtimeSessionCreateResponseModelGPTRealtime2_1Mini RealtimeSessionCreateResponseModel = "gpt-realtime-2.1-mini"
        
        const RealtimeSessionCreateResponseModelGPTRealtime2025_08_28 RealtimeSessionCreateResponseModel = "gpt-realtime-2025-08-28"
        
        const RealtimeSessionCreateResponseModelGPT4oRealtimePreview RealtimeSessionCreateResponseModel = "gpt-4o-realtime-preview"
        
        const RealtimeSessionCreateResponseModelGPT4oRealtimePreview2024_10_01 RealtimeSessionCreateResponseModel = "gpt-4o-realtime-preview-2024-10-01"
        
        const RealtimeSessionCreateResponseModelGPT4oRealtimePreview2024_12_17 RealtimeSessionCreateResponseModel = "gpt-4o-realtime-preview-2024-12-17"
        
        const RealtimeSessionCreateResponseModelGPT4oRealtimePreview2025_06_03 RealtimeSessionCreateResponseModel = "gpt-4o-realtime-preview-2025-06-03"
        
        const RealtimeSessionCreateResponseModelGPT4oMiniRealtimePreview RealtimeSessionCreateResponseModel = "gpt-4o-mini-realtime-preview"
        
        const RealtimeSessionCreateResponseModelGPT4oMiniRealtimePreview2024_12_17 RealtimeSessionCreateResponseModel = "gpt-4o-mini-realtime-preview-2024-12-17"
        
        const RealtimeSessionCreateResponseModelGPTRealtimeMini RealtimeSessionCreateResponseModel = "gpt-realtime-mini"
        
        const RealtimeSessionCreateResponseModelGPTRealtimeMini2025_10_06 RealtimeSessionCreateResponseModel = "gpt-realtime-mini-2025-10-06"
        
        const RealtimeSessionCreateResponseModelGPTRealtimeMini2025_12_15 RealtimeSessionCreateResponseModel = "gpt-realtime-mini-2025-12-15"
        
        const RealtimeSessionCreateResponseModelGPTAudio1_5 RealtimeSessionCreateResponseModel = "gpt-audio-1.5"
        
        const RealtimeSessionCreateResponseModelGPTAudioMini RealtimeSessionCreateResponseModel = "gpt-audio-mini"
        
        const RealtimeSessionCreateResponseModelGPTAudioMini2025_10_06 RealtimeSessionCreateResponseModel = "gpt-audio-mini-2025-10-06"
        
        const RealtimeSessionCreateResponseModelGPTAudioMini2025_12_15 RealtimeSessionCreateResponseModel = "gpt-audio-mini-2025-12-15"
    - OutputModalities []string
      
      The set of modalities the model can respond with. It defaults to ["audio"], indicating that the model will respond with audio plus a transcript. ["text"] can be used to make the model respond with text only. It is not possible to request both text and audio at the same time.
      - const RealtimeSessionCreateResponseOutputModalityText RealtimeSessionCreateResponseOutputModality = "text"
      - const RealtimeSessionCreateResponseOutputModalityAudio RealtimeSessionCreateResponseOutputModality = "audio"
    - Prompt ResponsePrompt
      
      Reference to a prompt template and its variables. Learn more.
      - ID string
        
        The unique identifier of the prompt template to use.
      - Variables map[string, ResponsePromptVariableUnion]
        
        Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.
        
        string
        
        type ResponseInputText struct{…}
        
        A text input to the model.
        
        Text string
        
        The text input to the model.
        
        Type InputText
        
        The type of the input item. Always input_text.
        
        const InputTextInputText InputText = "input_text"
        
        PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint
        
        Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
        
        Mode Explicit
        
        The breakpoint mode. Always explicit.
        
        const ExplicitExplicit Explicit = "explicit"
        
        type ResponseInputImage struct{…}
        
        An image input to the model. Learn about image inputs.
        
        Detail ResponseInputImageDetail
        
        The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.
        
        const ResponseInputImageDetailLow ResponseInputImageDetail = "low"
        
        const ResponseInputImageDetailHigh ResponseInputImageDetail = "high"
        
        const ResponseInputImageDetailAuto ResponseInputImageDetail = "auto"
        
        const ResponseInputImageDetailOriginal ResponseInputImageDetail = "original"
        
        Type InputImage
        
        The type of the input item. Always input_image.
        
        const InputImageInputImage InputImage = "input_image"
        
        FileID string
        
        The ID of the file to be sent to the model.
        
        ImageURL string
        
        The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.
        
        PromptCacheBreakpoint ResponseInputImagePromptCacheBreakpoint
        
        Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
        
        Mode Explicit
        
        The breakpoint mode. Always explicit.
        
        const ExplicitExplicit Explicit = "explicit"
        
        type ResponseInputFile struct{…}
        
        A file input to the model.
        
        Type InputFile
        
        The type of the input item. Always input_file.
        
        const InputFileInputFile InputFile = "input_file"
        
        Detail ResponseInputFileDetail
        
        The detail level of the file to be sent to the model. Use auto to let the system select the detail level; for GPT-5.6 and later models, auto uses high-quality rendering, which may increase input token usage. Use low for lower-cost rendering, or high to render the file at higher quality. Defaults to auto.
        
        const ResponseInputFileDetailAuto ResponseInputFileDetail = "auto"
        
        const ResponseInputFileDetailLow ResponseInputFileDetail = "low"
        
        const ResponseInputFileDetailHigh ResponseInputFileDetail = "high"
        
        FileData string
        
        The content of the file to be sent to the model.
        
        FileID string
        
        The ID of the file to be sent to the model.
        
        FileURL string
        
        The URL of the file to be sent to the model.
        
        Filename string
        
        The name of the file to be sent to the model.
        
        PromptCacheBreakpoint ResponseInputFilePromptCacheBreakpoint
        
        Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
        
        Mode Explicit
        
        The breakpoint mode. Always explicit.
        
        const ExplicitExplicit Explicit = "explicit"
      - Version string
        
        Optional version of the prompt template.
    - Reasoning RealtimeReasoning
      
      Configuration for reasoning-capable Realtime models such as gpt-realtime-2.
      - Effort RealtimeReasoningEffort
        
        Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.
        
        const RealtimeReasoningEffortMinimal RealtimeReasoningEffort = "minimal"
        
        const RealtimeReasoningEffortLow RealtimeReasoningEffort = "low"
        
        const RealtimeReasoningEffortMedium RealtimeReasoningEffort = "medium"
        
        const RealtimeReasoningEffortHigh RealtimeReasoningEffort = "high"
        
        const RealtimeReasoningEffortXhigh RealtimeReasoningEffort = "xhigh"
    - ToolChoice RealtimeSessionCreateResponseToolChoiceUnion
      
      How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.
      - type ToolChoiceOptions string
        
        Controls which (if any) tool is called by the model.
        
        none means the model will not call any tool and instead generates a message.
        
        auto means the model can pick between generating a message or calling one or more tools.
        
        required means the model must call one or more tools.
        
        const ToolChoiceOptionsNone ToolChoiceOptions = "none"
        
        const ToolChoiceOptionsAuto ToolChoiceOptions = "auto"
        
        const ToolChoiceOptionsRequired ToolChoiceOptions = "required"
      - type ToolChoiceFunction struct{…}
        
        Use this option to force the model to call a specific function.
        
        Name string
        
        The name of the function to call.
        
        Type Function
        
        For function calling, the type is always function.
        
        const FunctionFunction Function = "function"
      - type ToolChoiceMcp struct{…}
        
        Use this option to force the model to call a specific tool on a remote MCP server.
        
        ServerLabel string
        
        The label of the MCP server to use.
        
        Type Mcp
        
        For MCP tools, the type is always mcp.
        
        const McpMcp Mcp = "mcp"
        
        Name string
        
        The name of the tool to call on the server.
    - Tools []RealtimeSessionCreateResponseToolUnion
      
      Tools available to the model.
      - type RealtimeFunctionTool struct{…}
        
        Description string
        
        The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).
        
        Name string
        
        The name of the function.
        
        Parameters any
        
        Parameters of the function in JSON Schema.
        
        Type RealtimeFunctionToolType
        
        The type of the tool, i.e. function.
        
        const RealtimeFunctionToolTypeFunction RealtimeFunctionToolType = "function"
      - type RealtimeSessionCreateResponseToolMcpTool struct{…}
        
        Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.
        
        ServerLabel string
        
        A label for this MCP server, used to identify it in tool calls.
        
        Type Mcp
        
        The type of the MCP tool. Always mcp.
        
        const McpMcp Mcp = "mcp"
        
        AllowedCallers []string
        
        The tool invocation context(s).
        
        const RealtimeSessionCreateResponseToolMcpToolAllowedCallerDirect RealtimeSessionCreateResponseToolMcpToolAllowedCaller = "direct"
        
        const RealtimeSessionCreateResponseToolMcpToolAllowedCallerProgrammatic RealtimeSessionCreateResponseToolMcpToolAllowedCaller = "programmatic"
        
        AllowedTools RealtimeSessionCreateResponseToolMcpToolAllowedToolsUnion
        
        List of allowed tool names or a filter object.
        
        type RealtimeSessionCreateResponseToolMcpToolAllowedToolsMcpAllowedTools []string
        
        A string array of allowed tool names
        
        type RealtimeSessionCreateResponseToolMcpToolAllowedToolsMcpToolFilter struct{…}
        
        A filter object to specify which tools are allowed.
        
        ReadOnly bool
        
        Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.
        
        ToolNames []string
        
        List of allowed tool names.
        
        Authorization string
        
        An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.
        
        ConnectorID string
        
        Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.
        
        Currently supported connector_id values are:
        
        Dropbox: connector_dropbox
        
        Gmail: connector_gmail
        
        Google Calendar: connector_googlecalendar
        
        Google Drive: connector_googledrive
        
        Microsoft Teams: connector_microsoftteams
        
        Outlook Calendar: connector_outlookcalendar
        
        Outlook Email: connector_outlookemail
        
        SharePoint: connector_sharepoint
        
        const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorDropbox RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_dropbox"
        
        const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorGmail RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_gmail"
        
        const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorGooglecalendar RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_googlecalendar"
        
        const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorGoogledrive RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_googledrive"
        
        const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorMicrosoftteams RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_microsoftteams"
        
        const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorOutlookcalendar RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_outlookcalendar"
        
        const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorOutlookemail RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_outlookemail"
        
        const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorSharepoint RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_sharepoint"
        
        DeferLoading bool
        
        Whether this MCP tool is deferred and discovered via tool search.
        
        Headers map[string, string]
        
        Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.
        
        RequireApproval RealtimeSessionCreateResponseToolMcpToolRequireApprovalUnion
        
        Specify which of the MCP server's tools require approval.
        
        type RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalFilter struct{…}
        
        Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.
        
        Always RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalFilterAlways
        
        A filter object to specify which tools are allowed.
        
        ReadOnly bool
        
        Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.
        
        ToolNames []string
        
        List of allowed tool names.
        
        Never RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalFilterNever
        
        A filter object to specify which tools are allowed.
        
        ReadOnly bool
        
        Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.
        
        ToolNames []string
        
        List of allowed tool names.
        
        type RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalSetting string
        
        Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.
        
        const RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalSettingAlways RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalSetting = "always"
        
        const RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalSettingNever RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalSetting = "never"
        
        ServerDescription string
        
        Optional description of the MCP server, used to provide more context.
        
        ServerURL string
        
        The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.
        
        TunnelID string
        
        The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.
    - Tracing RealtimeSessionCreateResponseTracingUnion
      
      Realtime API can write session traces to the Traces Dashboard. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.
      
      auto will create a trace for the session with default values for the workflow name, group id, and metadata.
      - type Auto string
        
        Enables tracing and sets default values for tracing configuration options. Always auto.
        
        const AutoAuto Auto = "auto"
      - type RealtimeSessionCreateResponseTracingTracingConfiguration struct{…}
        
        Granular configuration for tracing.
        
        GroupID string
        
        The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.
        
        Metadata any
        
        The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.
        
        WorkflowName string
        
        The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.
    - Truncation RealtimeTruncationUnion
      
      When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.
      
      Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.
      
      Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.
      
      Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.
      - type RealtimeTruncationRealtimeTruncationStrategy string
        
        The truncation strategy to use for the session. auto is the default truncation strategy. disabled will disable truncation and emit errors when the conversation exceeds the input token limit.
        
        const RealtimeTruncationRealtimeTruncationStrategyAuto RealtimeTruncationRealtimeTruncationStrategy = "auto"
        
        const RealtimeTruncationRealtimeTruncationStrategyDisabled RealtimeTruncationRealtimeTruncationStrategy = "disabled"
      - type RealtimeTruncationRetentionRatio struct{…}
        
        Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.
        
        RetentionRatio float64
        
        Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.
        
        Type RetentionRatio
        
        Use retention ratio truncation.
        
        const RetentionRatioRetentionRatio RetentionRatio = "retention_ratio"
        
        TokenLimits RealtimeTruncationRetentionRatioTokenLimits
        
        Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.
        
        PostInstructions int64
        
        Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.
  - type RealtimeTranscriptionSessionCreateResponse struct{…}
    
    A Realtime transcription session configuration object.
    - ID string
      
      Unique identifier for the session that looks like sess_1234567890abcdef.
    - Object string
      
      The object type. Always realtime.transcription_session.
    - Type Transcription
      
      The type of session. Always transcription for transcription sessions.
      - const TranscriptionTranscription Transcription = "transcription"
    - Audio RealtimeTranscriptionSessionCreateResponseAudio
      
      Configuration for input audio for the session.
      - Input RealtimeTranscriptionSessionCreateResponseAudioInput
        
        Format RealtimeAudioFormatsUnion
        
        The PCM audio format. Only a 24kHz sample rate is supported.
        
        NoiseReduction RealtimeTranscriptionSessionCreateResponseAudioInputNoiseReduction
        
        Configuration for input audio noise reduction.
        
        Type NoiseReductionType
        
        Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.
        
        Transcription AudioTranscription
        
        TurnDetection RealtimeTranscriptionSessionTurnDetection
        
        Configuration for turn detection. Can be set to null to turn off. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech. For gpt-realtime-whisper, this must be null; VAD is not supported.
        
        PrefixPaddingMs int64
        
        Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.
        
        SilenceDurationMs int64
        
        Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.
        
        Threshold float64
        
        Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.
        
        Type string
        
        Type of turn detection, only server_vad is currently supported.
    - ExpiresAt int64
      
      Expiration timestamp for the session, in seconds since epoch.
    - Include []string
      
      Additional fields to include in server outputs.
      - item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.
      - const RealtimeTranscriptionSessionCreateResponseIncludeItemInputAudioTranscriptionLogprobs RealtimeTranscriptionSessionCreateResponseInclude = "item.input_audio_transcription.logprobs"
- Value string
  
  The generated client secret value.

Example

package main

import (
  "context"
  "fmt"

  "github.com/openai/openai-go"
  "github.com/openai/openai-go/option"
  "github.com/openai/openai-go/realtime"
)

func main() {
  client := openai.NewClient(
    option.WithAPIKey("My API Key"),
  )
  clientSecret, err := client.Realtime.ClientSecrets.New(context.TODO(), realtime.ClientSecretNewParams{

  })
  if err != nil {
    panic(err.Error())
  }
  fmt.Printf("%+v\n", clientSecret.ExpiresAt)
}

Response

{
  "expires_at": 0,
  "session": {
    "id": "id",
    "object": "realtime.session",
    "type": "realtime",
    "audio": {
      "input": {
        "format": {
          "rate": 24000,
          "type": "audio/pcm"
        },
        "noise_reduction": {
          "type": "near_field"
        },
        "transcription": {
          "delay": "minimal",
          "language": "language",
          "model": "whisper-1",
          "prompt": "prompt"
        },
        "turn_detection": {
          "type": "server_vad",
          "create_response": true,
          "idle_timeout_ms": 5000,
          "interrupt_response": true,
          "prefix_padding_ms": 0,
          "silence_duration_ms": 0,
          "threshold": 0
        }
      },
      "output": {
        "format": {
          "rate": 24000,
          "type": "audio/pcm"
        },
        "speed": 0.25,
        "voice": "ash"
      }
    },
    "expires_at": 0,
    "include": [
      "item.input_audio_transcription.logprobs"
    ],
    "instructions": "instructions",
    "max_output_tokens": "inf",
    "model": "gpt-realtime",
    "output_modalities": [
      "text"
    ],
    "prompt": {
      "id": "id",
      "variables": {
        "foo": "string"
      },
      "version": "version"
    },
    "reasoning": {
      "effort": "minimal"
    },
    "tool_choice": "none",
    "tools": [
      {
        "description": "description",
        "name": "name",
        "parameters": {},
        "type": "function"
      }
    ],
    "tracing": "auto",
    "truncation": "auto"
  },
  "value": "value"
}

Domain Types

Realtime Session Create Response

type RealtimeSessionCreateResponse struct{…}

A Realtime session configuration object.
- ID string
  
  Unique identifier for the session that looks like sess_1234567890abcdef.
- Object RealtimeSession
  
  The object type. Always realtime.session.
  - const RealtimeSessionRealtimeSession RealtimeSession = "realtime.session"
- Type Realtime
  
  The type of session to create. Always realtime for the Realtime API.
  - const RealtimeRealtime Realtime = "realtime"
- Audio RealtimeSessionCreateResponseAudio
  
  Configuration for input and output audio.
  - Input RealtimeSessionCreateResponseAudioInput
    - Format RealtimeAudioFormatsUnion
      
      The format of the input audio.
      - type RealtimeAudioFormatsAudioPCM struct{…}
        
        The PCM audio format. Only a 24kHz sample rate is supported.
        
        Rate int64
        
        The sample rate of the audio. Always 24000.
        
        const RealtimeAudioFormatsAudioPCMRate24000 RealtimeAudioFormatsAudioPCMRate = 24000
        
        Type string
        
        The audio format. Always audio/pcm.
        
        const RealtimeAudioFormatsAudioPCMTypeAudioPCM RealtimeAudioFormatsAudioPCMType = "audio/pcm"
      - type RealtimeAudioFormatsAudioPCMU struct{…}
        
        The G.711 μ-law format.
        
        Type string
        
        The audio format. Always audio/pcmu.
        
        const RealtimeAudioFormatsAudioPCMUTypeAudioPCMU RealtimeAudioFormatsAudioPCMUType = "audio/pcmu"
      - type RealtimeAudioFormatsAudioPCMA struct{…}
        
        The G.711 A-law format.
        
        Type string
        
        The audio format. Always audio/pcma.
        
        const RealtimeAudioFormatsAudioPCMATypeAudioPCMA RealtimeAudioFormatsAudioPCMAType = "audio/pcma"
    - NoiseReduction RealtimeSessionCreateResponseAudioInputNoiseReduction
      
      Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.
      - Type NoiseReductionType
        
        Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.
        
        const NoiseReductionTypeNearField NoiseReductionType = "near_field"
        
        const NoiseReductionTypeFarField NoiseReductionType = "far_field"
    - Transcription AudioTranscription
      - Delay AudioTranscriptionDelay
        
        Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.
        
        const AudioTranscriptionDelayMinimal AudioTranscriptionDelay = "minimal"
        
        const AudioTranscriptionDelayLow AudioTranscriptionDelay = "low"
        
        const AudioTranscriptionDelayMedium AudioTranscriptionDelay = "medium"
        
        const AudioTranscriptionDelayHigh AudioTranscriptionDelay = "high"
        
        const AudioTranscriptionDelayXhigh AudioTranscriptionDelay = "xhigh"
      - Language string
        
        The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.
      - Model AudioTranscriptionModel
        
        The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.
        
        string
        
        type AudioTranscriptionModel string
        
        The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.
        
        const AudioTranscriptionModelWhisper1 AudioTranscriptionModel = "whisper-1"
        
        const AudioTranscriptionModelGPT4oMiniTranscribe AudioTranscriptionModel = "gpt-4o-mini-transcribe"
        
        const AudioTranscriptionModelGPT4oMiniTranscribe2025_12_15 AudioTranscriptionModel = "gpt-4o-mini-transcribe-2025-12-15"
        
        const AudioTranscriptionModelGPT4oTranscribe AudioTranscriptionModel = "gpt-4o-transcribe"
        
        const AudioTranscriptionModelGPT4oTranscribeDiarize AudioTranscriptionModel = "gpt-4o-transcribe-diarize"
        
        const AudioTranscriptionModelGPTRealtimeWhisper AudioTranscriptionModel = "gpt-realtime-whisper"
      - Prompt string
        
        An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.
    - TurnDetection RealtimeSessionCreateResponseAudioInputTurnDetectionUnion
      
      Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.
      
      Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.
      
      Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.
      
      For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.
      - type RealtimeSessionCreateResponseAudioInputTurnDetectionServerVad struct{…}
        
        Server-side voice activity detection (VAD) which flips on when user speech is detected and off after a period of silence.
        
        Type ServerVad
        
        Type of turn detection, server_vad to turn on simple Server VAD.
        
        const ServerVadServerVad ServerVad = "server_vad"
        
        CreateResponse bool
        
        Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.
        
        If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.
        
        IdleTimeoutMs int64
        
        Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.
        
        The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.
        
        An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.
        
        InterruptResponse bool
        
        Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.
        
        If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.
        
        PrefixPaddingMs int64
        
        Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.
        
        SilenceDurationMs int64
        
        Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.
        
        Threshold float64
        
        Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.
      - type RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVad struct{…}
        
        Server-side semantic turn detection which uses a model to determine when the user has finished speaking.
        
        Type SemanticVad
        
        Type of turn detection, semantic_vad to turn on Semantic VAD.
        
        const SemanticVadSemanticVad SemanticVad = "semantic_vad"
        
        CreateResponse bool
        
        Whether or not to automatically generate a response when a VAD stop event occurs.
        
        Eagerness string
        
        Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.
        
        const RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagernessLow RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagerness = "low"
        
        const RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagernessMedium RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagerness = "medium"
        
        const RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagernessHigh RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagerness = "high"
        
        const RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagernessAuto RealtimeSessionCreateResponseAudioInputTurnDetectionSemanticVadEagerness = "auto"
        
        InterruptResponse bool
        
        Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.
  - Output RealtimeSessionCreateResponseAudioOutput
    - Format RealtimeAudioFormatsUnion
      
      The format of the output audio.
    - Speed float64
      
      The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.
      
      This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.
    - Voice string
      
      The voice the model uses to respond. Voice cannot be changed during the session once the model has responded with audio at least once. Current voice options are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. We recommend marin and cedar for best quality.
      - string
      - string
        
        const RealtimeSessionCreateResponseAudioOutputVoiceAlloy RealtimeSessionCreateResponseAudioOutputVoice = "alloy"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceAsh RealtimeSessionCreateResponseAudioOutputVoice = "ash"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceBallad RealtimeSessionCreateResponseAudioOutputVoice = "ballad"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceCoral RealtimeSessionCreateResponseAudioOutputVoice = "coral"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceEcho RealtimeSessionCreateResponseAudioOutputVoice = "echo"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceSage RealtimeSessionCreateResponseAudioOutputVoice = "sage"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceShimmer RealtimeSessionCreateResponseAudioOutputVoice = "shimmer"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceVerse RealtimeSessionCreateResponseAudioOutputVoice = "verse"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceMarin RealtimeSessionCreateResponseAudioOutputVoice = "marin"
        
        const RealtimeSessionCreateResponseAudioOutputVoiceCedar RealtimeSessionCreateResponseAudioOutputVoice = "cedar"
- ExpiresAt int64
  
  Expiration timestamp for the session, in seconds since epoch.
- Include []string
  
  Additional fields to include in server outputs.
  
  item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.
  - const RealtimeSessionCreateResponseIncludeItemInputAudioTranscriptionLogprobs RealtimeSessionCreateResponseInclude = "item.input_audio_transcription.logprobs"
- Instructions string
  
  The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.
  
  Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.
- MaxOutputTokens RealtimeSessionCreateResponseMaxOutputTokensUnion
  
  Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.
  - int64
  - type Inf string
    - const InfInf Inf = "inf"
- Model RealtimeSessionCreateResponseModel
  
  The Realtime model used for this session.
  - string
  - type RealtimeSessionCreateResponseModel string
    
    The Realtime model used for this session.
    - const RealtimeSessionCreateResponseModelGPTRealtime RealtimeSessionCreateResponseModel = "gpt-realtime"
    - const RealtimeSessionCreateResponseModelGPTRealtime1_5 RealtimeSessionCreateResponseModel = "gpt-realtime-1.5"
    - const RealtimeSessionCreateResponseModelGPTRealtime2 RealtimeSessionCreateResponseModel = "gpt-realtime-2"
    - const RealtimeSessionCreateResponseModelGPTRealtime2_1 RealtimeSessionCreateResponseModel = "gpt-realtime-2.1"
    - const RealtimeSessionCreateResponseModelGPTRealtime2_1Mini RealtimeSessionCreateResponseModel = "gpt-realtime-2.1-mini"
    - const RealtimeSessionCreateResponseModelGPTRealtime2025_08_28 RealtimeSessionCreateResponseModel = "gpt-realtime-2025-08-28"
    - const RealtimeSessionCreateResponseModelGPT4oRealtimePreview RealtimeSessionCreateResponseModel = "gpt-4o-realtime-preview"
    - const RealtimeSessionCreateResponseModelGPT4oRealtimePreview2024_10_01 RealtimeSessionCreateResponseModel = "gpt-4o-realtime-preview-2024-10-01"
    - const RealtimeSessionCreateResponseModelGPT4oRealtimePreview2024_12_17 RealtimeSessionCreateResponseModel = "gpt-4o-realtime-preview-2024-12-17"
    - const RealtimeSessionCreateResponseModelGPT4oRealtimePreview2025_06_03 RealtimeSessionCreateResponseModel = "gpt-4o-realtime-preview-2025-06-03"
    - const RealtimeSessionCreateResponseModelGPT4oMiniRealtimePreview RealtimeSessionCreateResponseModel = "gpt-4o-mini-realtime-preview"
    - const RealtimeSessionCreateResponseModelGPT4oMiniRealtimePreview2024_12_17 RealtimeSessionCreateResponseModel = "gpt-4o-mini-realtime-preview-2024-12-17"
    - const RealtimeSessionCreateResponseModelGPTRealtimeMini RealtimeSessionCreateResponseModel = "gpt-realtime-mini"
    - const RealtimeSessionCreateResponseModelGPTRealtimeMini2025_10_06 RealtimeSessionCreateResponseModel = "gpt-realtime-mini-2025-10-06"
    - const RealtimeSessionCreateResponseModelGPTRealtimeMini2025_12_15 RealtimeSessionCreateResponseModel = "gpt-realtime-mini-2025-12-15"
    - const RealtimeSessionCreateResponseModelGPTAudio1_5 RealtimeSessionCreateResponseModel = "gpt-audio-1.5"
    - const RealtimeSessionCreateResponseModelGPTAudioMini RealtimeSessionCreateResponseModel = "gpt-audio-mini"
    - const RealtimeSessionCreateResponseModelGPTAudioMini2025_10_06 RealtimeSessionCreateResponseModel = "gpt-audio-mini-2025-10-06"
    - const RealtimeSessionCreateResponseModelGPTAudioMini2025_12_15 RealtimeSessionCreateResponseModel = "gpt-audio-mini-2025-12-15"
- OutputModalities []string
  
  The set of modalities the model can respond with. It defaults to ["audio"], indicating that the model will respond with audio plus a transcript. ["text"] can be used to make the model respond with text only. It is not possible to request both text and audio at the same time.
  - const RealtimeSessionCreateResponseOutputModalityText RealtimeSessionCreateResponseOutputModality = "text"
  - const RealtimeSessionCreateResponseOutputModalityAudio RealtimeSessionCreateResponseOutputModality = "audio"
- Prompt ResponsePrompt
  
  Reference to a prompt template and its variables. Learn more.
  - ID string
    
    The unique identifier of the prompt template to use.
  - Variables map[string, ResponsePromptVariableUnion]
    
    Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.
    - string
    - type ResponseInputText struct{…}
      
      A text input to the model.
      - Text string
        
        The text input to the model.
      - Type InputText
        
        The type of the input item. Always input_text.
        
        const InputTextInputText InputText = "input_text"
      - PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint
        
        Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
        
        Mode Explicit
        
        The breakpoint mode. Always explicit.
        
        const ExplicitExplicit Explicit = "explicit"
    - type ResponseInputImage struct{…}
      
      An image input to the model. Learn about image inputs.
      - Detail ResponseInputImageDetail
        
        The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.
        
        const ResponseInputImageDetailLow ResponseInputImageDetail = "low"
        
        const ResponseInputImageDetailHigh ResponseInputImageDetail = "high"
        
        const ResponseInputImageDetailAuto ResponseInputImageDetail = "auto"
        
        const ResponseInputImageDetailOriginal ResponseInputImageDetail = "original"
      - Type InputImage
        
        The type of the input item. Always input_image.
        
        const InputImageInputImage InputImage = "input_image"
      - FileID string
        
        The ID of the file to be sent to the model.
      - ImageURL string
        
        The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.
      - PromptCacheBreakpoint ResponseInputImagePromptCacheBreakpoint
        
        Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
        
        Mode Explicit
        
        The breakpoint mode. Always explicit.
        
        const ExplicitExplicit Explicit = "explicit"
    - type ResponseInputFile struct{…}
      
      A file input to the model.
      - Type InputFile
        
        The type of the input item. Always input_file.
        
        const InputFileInputFile InputFile = "input_file"
      - Detail ResponseInputFileDetail
        
        The detail level of the file to be sent to the model. Use auto to let the system select the detail level; for GPT-5.6 and later models, auto uses high-quality rendering, which may increase input token usage. Use low for lower-cost rendering, or high to render the file at higher quality. Defaults to auto.
        
        const ResponseInputFileDetailAuto ResponseInputFileDetail = "auto"
        
        const ResponseInputFileDetailLow ResponseInputFileDetail = "low"
        
        const ResponseInputFileDetailHigh ResponseInputFileDetail = "high"
      - FileData string
        
        The content of the file to be sent to the model.
      - FileID string
        
        The ID of the file to be sent to the model.
      - FileURL string
        
        The URL of the file to be sent to the model.
      - Filename string
        
        The name of the file to be sent to the model.
      - PromptCacheBreakpoint ResponseInputFilePromptCacheBreakpoint
        
        Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
        
        Mode Explicit
        
        The breakpoint mode. Always explicit.
        
        const ExplicitExplicit Explicit = "explicit"
  - Version string
    
    Optional version of the prompt template.
- Reasoning RealtimeReasoning
  
  Configuration for reasoning-capable Realtime models such as gpt-realtime-2.
  - Effort RealtimeReasoningEffort
    
    Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.
    - const RealtimeReasoningEffortMinimal RealtimeReasoningEffort = "minimal"
    - const RealtimeReasoningEffortLow RealtimeReasoningEffort = "low"
    - const RealtimeReasoningEffortMedium RealtimeReasoningEffort = "medium"
    - const RealtimeReasoningEffortHigh RealtimeReasoningEffort = "high"
    - const RealtimeReasoningEffortXhigh RealtimeReasoningEffort = "xhigh"
- ToolChoice RealtimeSessionCreateResponseToolChoiceUnion
  
  How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.
  - type ToolChoiceOptions string
    
    Controls which (if any) tool is called by the model.
    
    none means the model will not call any tool and instead generates a message.
    
    auto means the model can pick between generating a message or calling one or more tools.
    
    required means the model must call one or more tools.
    - const ToolChoiceOptionsNone ToolChoiceOptions = "none"
    - const ToolChoiceOptionsAuto ToolChoiceOptions = "auto"
    - const ToolChoiceOptionsRequired ToolChoiceOptions = "required"
  - type ToolChoiceFunction struct{…}
    
    Use this option to force the model to call a specific function.
    - Name string
      
      The name of the function to call.
    - Type Function
      
      For function calling, the type is always function.
      - const FunctionFunction Function = "function"
  - type ToolChoiceMcp struct{…}
    
    Use this option to force the model to call a specific tool on a remote MCP server.
    - ServerLabel string
      
      The label of the MCP server to use.
    - Type Mcp
      
      For MCP tools, the type is always mcp.
      - const McpMcp Mcp = "mcp"
    - Name string
      
      The name of the tool to call on the server.
- Tools []RealtimeSessionCreateResponseToolUnion
  
  Tools available to the model.
  - type RealtimeFunctionTool struct{…}
    - Description string
      
      The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).
    - Name string
      
      The name of the function.
    - Parameters any
      
      Parameters of the function in JSON Schema.
    - Type RealtimeFunctionToolType
      
      The type of the tool, i.e. function.
      - const RealtimeFunctionToolTypeFunction RealtimeFunctionToolType = "function"
  - type RealtimeSessionCreateResponseToolMcpTool struct{…}
    
    Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.
    - ServerLabel string
      
      A label for this MCP server, used to identify it in tool calls.
    - Type Mcp
      
      The type of the MCP tool. Always mcp.
      - const McpMcp Mcp = "mcp"
    - AllowedCallers []string
      
      The tool invocation context(s).
      - const RealtimeSessionCreateResponseToolMcpToolAllowedCallerDirect RealtimeSessionCreateResponseToolMcpToolAllowedCaller = "direct"
      - const RealtimeSessionCreateResponseToolMcpToolAllowedCallerProgrammatic RealtimeSessionCreateResponseToolMcpToolAllowedCaller = "programmatic"
    - AllowedTools RealtimeSessionCreateResponseToolMcpToolAllowedToolsUnion
      
      List of allowed tool names or a filter object.
      - type RealtimeSessionCreateResponseToolMcpToolAllowedToolsMcpAllowedTools []string
        
        A string array of allowed tool names
      - type RealtimeSessionCreateResponseToolMcpToolAllowedToolsMcpToolFilter struct{…}
        
        A filter object to specify which tools are allowed.
        
        ReadOnly bool
        
        Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.
        
        ToolNames []string
        
        List of allowed tool names.
    - Authorization string
      
      An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.
    - ConnectorID string
      
      Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.
      
      Currently supported connector_id values are:
      - Dropbox: connector_dropbox
      - Gmail: connector_gmail
      - Google Calendar: connector_googlecalendar
      - Google Drive: connector_googledrive
      - Microsoft Teams: connector_microsoftteams
      - Outlook Calendar: connector_outlookcalendar
      - Outlook Email: connector_outlookemail
      - SharePoint: connector_sharepoint
      - const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorDropbox RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_dropbox"
      - const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorGmail RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_gmail"
      - const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorGooglecalendar RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_googlecalendar"
      - const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorGoogledrive RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_googledrive"
      - const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorMicrosoftteams RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_microsoftteams"
      - const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorOutlookcalendar RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_outlookcalendar"
      - const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorOutlookemail RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_outlookemail"
      - const RealtimeSessionCreateResponseToolMcpToolConnectorIDConnectorSharepoint RealtimeSessionCreateResponseToolMcpToolConnectorID = "connector_sharepoint"
    - DeferLoading bool
      
      Whether this MCP tool is deferred and discovered via tool search.
    - Headers map[string, string]
      
      Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.
    - RequireApproval RealtimeSessionCreateResponseToolMcpToolRequireApprovalUnion
      
      Specify which of the MCP server's tools require approval.
      - type RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalFilter struct{…}
        
        Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.
        
        Always RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalFilterAlways
        
        A filter object to specify which tools are allowed.
        
        ReadOnly bool
        
        Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.
        
        ToolNames []string
        
        List of allowed tool names.
        
        Never RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalFilterNever
        
        A filter object to specify which tools are allowed.
        
        ReadOnly bool
        
        Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.
        
        ToolNames []string
        
        List of allowed tool names.
      - type RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalSetting string
        
        Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.
        
        const RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalSettingAlways RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalSetting = "always"
        
        const RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalSettingNever RealtimeSessionCreateResponseToolMcpToolRequireApprovalMcpToolApprovalSetting = "never"
    - ServerDescription string
      
      Optional description of the MCP server, used to provide more context.
    - ServerURL string
      
      The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.
    - TunnelID string
      
      The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.
- Tracing RealtimeSessionCreateResponseTracingUnion
  
  Realtime API can write session traces to the Traces Dashboard. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.
  
  auto will create a trace for the session with default values for the workflow name, group id, and metadata.
  - type Auto string
    
    Enables tracing and sets default values for tracing configuration options. Always auto.
    - const AutoAuto Auto = "auto"
  - type RealtimeSessionCreateResponseTracingTracingConfiguration struct{…}
    
    Granular configuration for tracing.
    - GroupID string
      
      The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.
    - Metadata any
      
      The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.
    - WorkflowName string
      
      The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.
- Truncation RealtimeTruncationUnion
  
  When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.
  
  Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.
  
  Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.
  
  Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.
  - type RealtimeTruncationRealtimeTruncationStrategy string
    
    The truncation strategy to use for the session. auto is the default truncation strategy. disabled will disable truncation and emit errors when the conversation exceeds the input token limit.
    - const RealtimeTruncationRealtimeTruncationStrategyAuto RealtimeTruncationRealtimeTruncationStrategy = "auto"
    - const RealtimeTruncationRealtimeTruncationStrategyDisabled RealtimeTruncationRealtimeTruncationStrategy = "disabled"
  - type RealtimeTruncationRetentionRatio struct{…}
    
    Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.
    - RetentionRatio float64
      
      Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.
    - Type RetentionRatio
      
      Use retention ratio truncation.
      - const RetentionRatioRetentionRatio RetentionRatio = "retention_ratio"
    - TokenLimits RealtimeTruncationRetentionRatioTokenLimits
      
      Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.
      - PostInstructions int64
        
        Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.

Realtime Transcription Session Create Response

type RealtimeTranscriptionSessionCreateResponse struct{…}

A Realtime transcription session configuration object.
- ID string
  
  Unique identifier for the session that looks like sess_1234567890abcdef.
- Object string
  
  The object type. Always realtime.transcription_session.
- Type Transcription
  
  The type of session. Always transcription for transcription sessions.
  - const TranscriptionTranscription Transcription = "transcription"
- Audio RealtimeTranscriptionSessionCreateResponseAudio
  
  Configuration for input audio for the session.
  - Input RealtimeTranscriptionSessionCreateResponseAudioInput
    - Format RealtimeAudioFormatsUnion
      
      The PCM audio format. Only a 24kHz sample rate is supported.
      - type RealtimeAudioFormatsAudioPCM struct{…}
        
        The PCM audio format. Only a 24kHz sample rate is supported.
        
        Rate int64
        
        The sample rate of the audio. Always 24000.
        
        const RealtimeAudioFormatsAudioPCMRate24000 RealtimeAudioFormatsAudioPCMRate = 24000
        
        Type string
        
        The audio format. Always audio/pcm.
        
        const RealtimeAudioFormatsAudioPCMTypeAudioPCM RealtimeAudioFormatsAudioPCMType = "audio/pcm"
      - type RealtimeAudioFormatsAudioPCMU struct{…}
        
        The G.711 μ-law format.
        
        Type string
        
        The audio format. Always audio/pcmu.
        
        const RealtimeAudioFormatsAudioPCMUTypeAudioPCMU RealtimeAudioFormatsAudioPCMUType = "audio/pcmu"
      - type RealtimeAudioFormatsAudioPCMA struct{…}
        
        The G.711 A-law format.
        
        Type string
        
        The audio format. Always audio/pcma.
        
        const RealtimeAudioFormatsAudioPCMATypeAudioPCMA RealtimeAudioFormatsAudioPCMAType = "audio/pcma"
    - NoiseReduction RealtimeTranscriptionSessionCreateResponseAudioInputNoiseReduction
      
      Configuration for input audio noise reduction.
      - Type NoiseReductionType
        
        Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.
        
        const NoiseReductionTypeNearField NoiseReductionType = "near_field"
        
        const NoiseReductionTypeFarField NoiseReductionType = "far_field"
    - Transcription AudioTranscription
      - Delay AudioTranscriptionDelay
        
        Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.
        
        const AudioTranscriptionDelayMinimal AudioTranscriptionDelay = "minimal"
        
        const AudioTranscriptionDelayLow AudioTranscriptionDelay = "low"
        
        const AudioTranscriptionDelayMedium AudioTranscriptionDelay = "medium"
        
        const AudioTranscriptionDelayHigh AudioTranscriptionDelay = "high"
        
        const AudioTranscriptionDelayXhigh AudioTranscriptionDelay = "xhigh"
      - Language string
        
        The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.
      - Model AudioTranscriptionModel
        
        The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.
        
        string
        
        type AudioTranscriptionModel string
        
        The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.
        
        const AudioTranscriptionModelWhisper1 AudioTranscriptionModel = "whisper-1"
        
        const AudioTranscriptionModelGPT4oMiniTranscribe AudioTranscriptionModel = "gpt-4o-mini-transcribe"
        
        const AudioTranscriptionModelGPT4oMiniTranscribe2025_12_15 AudioTranscriptionModel = "gpt-4o-mini-transcribe-2025-12-15"
        
        const AudioTranscriptionModelGPT4oTranscribe AudioTranscriptionModel = "gpt-4o-transcribe"
        
        const AudioTranscriptionModelGPT4oTranscribeDiarize AudioTranscriptionModel = "gpt-4o-transcribe-diarize"
        
        const AudioTranscriptionModelGPTRealtimeWhisper AudioTranscriptionModel = "gpt-realtime-whisper"
      - Prompt string
        
        An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.
    - TurnDetection RealtimeTranscriptionSessionTurnDetection
      
      Configuration for turn detection. Can be set to null to turn off. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech. For gpt-realtime-whisper, this must be null; VAD is not supported.
      - PrefixPaddingMs int64
        
        Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.
      - SilenceDurationMs int64
        
        Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.
      - Threshold float64
        
        Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.
      - Type string
        
        Type of turn detection, only server_vad is currently supported.
- ExpiresAt int64
  
  Expiration timestamp for the session, in seconds since epoch.
- Include []string
  
  Additional fields to include in server outputs.
  - item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.
  - const RealtimeTranscriptionSessionCreateResponseIncludeItemInputAudioTranscriptionLogprobs RealtimeTranscriptionSessionCreateResponseInclude = "item.input_audio_transcription.logprobs"

Realtime Transcription Session Turn Detection

type RealtimeTranscriptionSessionTurnDetection struct{…}

Configuration for turn detection. Can be set to null to turn off. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech. For gpt-realtime-whisper, this must be null; VAD is not supported.
- PrefixPaddingMs int64
  
  Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.
- SilenceDurationMs int64
  
  Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.
- Threshold float64
  
  Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.
- Type string
  
  Type of turn detection, only server_vad is currently supported.

go/resources/realtime/subresources/client_secrets/index.md +136 −16

6 6

7**post** `/realtime/client_secrets`7**post** `/realtime/client_secrets`

8 8

~~9Create a Realtime client secret with an associated session configuration.~~9Create client secret

~~11Client secrets are short-lived tokens that can be passed to a client app,~~

~~12such as a web frontend or mobile client, which grants access to the Realtime API without~~

~~13leaking your main API key. You can configure a custom TTL for each client secret.~~

~~15You can also attach session configuration options to the client secret, which will be~~

~~16applied to any sessions created using that client secret, but these can also be overridden~~

~~17by the client connection.~~

~~19[Learn more about authentication with client secrets over WebRTC](https://platform.openai.com/docs/guides/realtime-webrtc).~~

~~21Returns the created client secret and the effective session object. The client secret is a string that looks like `ek_1234`.~~

22 10

23### Parameters11### Parameters

24 12

358 346

359 - `const RealtimeSessionCreateRequestModelGPTRealtime2 RealtimeSessionCreateRequestModel = "gpt-realtime-2"`347 - `const RealtimeSessionCreateRequestModelGPTRealtime2 RealtimeSessionCreateRequestModel = "gpt-realtime-2"`

360 348

349 - `const RealtimeSessionCreateRequestModelGPTRealtime2_1 RealtimeSessionCreateRequestModel = "gpt-realtime-2.1"`

350

351 - `const RealtimeSessionCreateRequestModelGPTRealtime2_1Mini RealtimeSessionCreateRequestModel = "gpt-realtime-2.1-mini"`

352

361 - `const RealtimeSessionCreateRequestModelGPTRealtime2025_08_28 RealtimeSessionCreateRequestModel = "gpt-realtime-2025-08-28"`353 - `const RealtimeSessionCreateRequestModelGPTRealtime2025_08_28 RealtimeSessionCreateRequestModel = "gpt-realtime-2025-08-28"`

362 354

363 - `const RealtimeSessionCreateRequestModelGPT4oRealtimePreview RealtimeSessionCreateRequestModel = "gpt-4o-realtime-preview"`355 - `const RealtimeSessionCreateRequestModelGPT4oRealtimePreview RealtimeSessionCreateRequestModel = "gpt-4o-realtime-preview"`

432 424

433 - `const InputTextInputText InputText = "input_text"`425 - `const InputTextInputText InputText = "input_text"`

434 426

427 - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint`

428

429 Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.

430

431 - `Mode Explicit`

432

433 The breakpoint mode. Always `explicit`.

434

435 - `const ExplicitExplicit Explicit = "explicit"`

436

435 - `type ResponseInputImage struct{…}`437 - `type ResponseInputImage struct{…}`

436 438

437 An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision).439 An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision).

462 464

463 The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.465 The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

464 466

467 - `PromptCacheBreakpoint ResponseInputImagePromptCacheBreakpoint`

468

469 Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.

470

471 - `Mode Explicit`

472

473 The breakpoint mode. Always `explicit`.

474

475 - `const ExplicitExplicit Explicit = "explicit"`

476

465 - `type ResponseInputFile struct{…}`477 - `type ResponseInputFile struct{…}`

466 478

467 A file input to the model.479 A file input to the model.

474 486

475 - `Detail ResponseInputFileDetail`487 - `Detail ResponseInputFileDetail`

476 488

477 The detail level of the file to be sent to the model. Use `low` for the default rendering behavior, or `high` to render the file at higher quality. Defaults to `low`.489 The detail level of the file to be sent to the model. Use `auto` to let the system select the detail level; for GPT-5.6 and later models, `auto` uses high-quality rendering, which may increase input token usage. Use `low` for lower-cost rendering, or `high` to render the file at higher quality. Defaults to `auto`.

490

491 - `const ResponseInputFileDetailAuto ResponseInputFileDetail = "auto"`

478 492

479 - `const ResponseInputFileDetailLow ResponseInputFileDetail = "low"`493 - `const ResponseInputFileDetailLow ResponseInputFileDetail = "low"`

480 494

496 510

497 The name of the file to be sent to the model.511 The name of the file to be sent to the model.

498 512

513 - `PromptCacheBreakpoint ResponseInputFilePromptCacheBreakpoint`

514

515 Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.

516

517 - `Mode Explicit`

518

519 The breakpoint mode. Always `explicit`.

520

521 - `const ExplicitExplicit Explicit = "explicit"`

522

499 - `Version string`523 - `Version string`

500 524

501 Optional version of the prompt template.525 Optional version of the prompt template.

611 635

612 - `const McpMcp Mcp = "mcp"`636 - `const McpMcp Mcp = "mcp"`

613 637

638 - `AllowedCallers []string`

639

640 The tool invocation context(s).

641

642 - `const RealtimeToolsConfigUnionMcpAllowedCallerDirect RealtimeToolsConfigUnionMcpAllowedCaller = "direct"`

643

644 - `const RealtimeToolsConfigUnionMcpAllowedCallerProgrammatic RealtimeToolsConfigUnionMcpAllowedCaller = "programmatic"`

645

614 - `AllowedTools RealtimeToolsConfigUnionMcpAllowedTools`646 - `AllowedTools RealtimeToolsConfigUnionMcpAllowedTools`

615 647

616 List of allowed tool names or a filter object.648 List of allowed tool names or a filter object.

1271 1303

1272 - `const RealtimeSessionCreateResponseModelGPTRealtime2 RealtimeSessionCreateResponseModel = "gpt-realtime-2"`1304 - `const RealtimeSessionCreateResponseModelGPTRealtime2 RealtimeSessionCreateResponseModel = "gpt-realtime-2"`

1273 1305

1306 - `const RealtimeSessionCreateResponseModelGPTRealtime2_1 RealtimeSessionCreateResponseModel = "gpt-realtime-2.1"`

1307

1308 - `const RealtimeSessionCreateResponseModelGPTRealtime2_1Mini RealtimeSessionCreateResponseModel = "gpt-realtime-2.1-mini"`

1309

1274 - `const RealtimeSessionCreateResponseModelGPTRealtime2025_08_28 RealtimeSessionCreateResponseModel = "gpt-realtime-2025-08-28"`1310 - `const RealtimeSessionCreateResponseModelGPTRealtime2025_08_28 RealtimeSessionCreateResponseModel = "gpt-realtime-2025-08-28"`

1275 1311

1276 - `const RealtimeSessionCreateResponseModelGPT4oRealtimePreview RealtimeSessionCreateResponseModel = "gpt-4o-realtime-preview"`1312 - `const RealtimeSessionCreateResponseModelGPT4oRealtimePreview RealtimeSessionCreateResponseModel = "gpt-4o-realtime-preview"`

1340 1376

1341 - `const InputTextInputText InputText = "input_text"`1377 - `const InputTextInputText InputText = "input_text"`

1342 1378

1379 - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint`

1380

1381 Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.

1382

1383 - `Mode Explicit`

1384

1385 The breakpoint mode. Always `explicit`.

1386

1387 - `const ExplicitExplicit Explicit = "explicit"`

1388

1343 - `type ResponseInputImage struct{…}`1389 - `type ResponseInputImage struct{…}`

1344 1390

1345 An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision).1391 An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision).

1370 1416

1371 The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.1417 The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

1372 1418

1419 - `PromptCacheBreakpoint ResponseInputImagePromptCacheBreakpoint`

1420

1421 Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.

1422

1423 - `Mode Explicit`

1424

1425 The breakpoint mode. Always `explicit`.

1426

1427 - `const ExplicitExplicit Explicit = "explicit"`

1428

1373 - `type ResponseInputFile struct{…}`1429 - `type ResponseInputFile struct{…}`

1374 1430

1375 A file input to the model.1431 A file input to the model.

1382 1438

1383 - `Detail ResponseInputFileDetail`1439 - `Detail ResponseInputFileDetail`

1384 1440

1385 The detail level of the file to be sent to the model. Use `low` for the default rendering behavior, or `high` to render the file at higher quality. Defaults to `low`.1441 The detail level of the file to be sent to the model. Use `auto` to let the system select the detail level; for GPT-5.6 and later models, `auto` uses high-quality rendering, which may increase input token usage. Use `low` for lower-cost rendering, or `high` to render the file at higher quality. Defaults to `auto`.

1442

1443 - `const ResponseInputFileDetailAuto ResponseInputFileDetail = "auto"`

1386 1444

1387 - `const ResponseInputFileDetailLow ResponseInputFileDetail = "low"`1445 - `const ResponseInputFileDetailLow ResponseInputFileDetail = "low"`

1388 1446

1404 1462

1405 The name of the file to be sent to the model.1463 The name of the file to be sent to the model.

1406 1464

1465 - `PromptCacheBreakpoint ResponseInputFilePromptCacheBreakpoint`

1466

1467 Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.

1468

1469 - `Mode Explicit`

1470

1471 The breakpoint mode. Always `explicit`.

1472

1473 - `const ExplicitExplicit Explicit = "explicit"`

1474

1407 - `Version string`1475 - `Version string`

1408 1476

1409 Optional version of the prompt template.1477 Optional version of the prompt template.

1522 1590

1523 - `const McpMcp Mcp = "mcp"`1591 - `const McpMcp Mcp = "mcp"`

1524 1592

1593 - `AllowedCallers []string`

1594

1595 The tool invocation context(s).

1596

1597 - `const RealtimeSessionCreateResponseToolMcpToolAllowedCallerDirect RealtimeSessionCreateResponseToolMcpToolAllowedCaller = "direct"`

1598

1599 - `const RealtimeSessionCreateResponseToolMcpToolAllowedCallerProgrammatic RealtimeSessionCreateResponseToolMcpToolAllowedCaller = "programmatic"`

1600

1525 - `AllowedTools RealtimeSessionCreateResponseToolMcpToolAllowedToolsUnion`1601 - `AllowedTools RealtimeSessionCreateResponseToolMcpToolAllowedToolsUnion`

1526 1602

1527 List of allowed tool names or a filter object.1603 List of allowed tool names or a filter object.

2242 2318

2243 - `const RealtimeSessionCreateResponseModelGPTRealtime2 RealtimeSessionCreateResponseModel = "gpt-realtime-2"`2319 - `const RealtimeSessionCreateResponseModelGPTRealtime2 RealtimeSessionCreateResponseModel = "gpt-realtime-2"`

2244 2320

2321 - `const RealtimeSessionCreateResponseModelGPTRealtime2_1 RealtimeSessionCreateResponseModel = "gpt-realtime-2.1"`

2322

2323 - `const RealtimeSessionCreateResponseModelGPTRealtime2_1Mini RealtimeSessionCreateResponseModel = "gpt-realtime-2.1-mini"`

2324

2245 - `const RealtimeSessionCreateResponseModelGPTRealtime2025_08_28 RealtimeSessionCreateResponseModel = "gpt-realtime-2025-08-28"`2325 - `const RealtimeSessionCreateResponseModelGPTRealtime2025_08_28 RealtimeSessionCreateResponseModel = "gpt-realtime-2025-08-28"`

2246 2326

2247 - `const RealtimeSessionCreateResponseModelGPT4oRealtimePreview RealtimeSessionCreateResponseModel = "gpt-4o-realtime-preview"`2327 - `const RealtimeSessionCreateResponseModelGPT4oRealtimePreview RealtimeSessionCreateResponseModel = "gpt-4o-realtime-preview"`

2311 2391

2312 - `const InputTextInputText InputText = "input_text"`2392 - `const InputTextInputText InputText = "input_text"`

2313 2393

2394 - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint`

2395

2396 Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.

2397

2398 - `Mode Explicit`

2399

2400 The breakpoint mode. Always `explicit`.

2401

2402 - `const ExplicitExplicit Explicit = "explicit"`

2403

2314 - `type ResponseInputImage struct{…}`2404 - `type ResponseInputImage struct{…}`

2315 2405

2316 An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision).2406 An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision).

2341 2431

2342 The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.2432 The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

2343 2433

2434 - `PromptCacheBreakpoint ResponseInputImagePromptCacheBreakpoint`

2435

2436 Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.

2437

2438 - `Mode Explicit`

2439

2440 The breakpoint mode. Always `explicit`.

2441

2442 - `const ExplicitExplicit Explicit = "explicit"`

2443

2344 - `type ResponseInputFile struct{…}`2444 - `type ResponseInputFile struct{…}`

2345 2445

2346 A file input to the model.2446 A file input to the model.

2353 2453

2354 - `Detail ResponseInputFileDetail`2454 - `Detail ResponseInputFileDetail`

2355 2455

2356 The detail level of the file to be sent to the model. Use `low` for the default rendering behavior, or `high` to render the file at higher quality. Defaults to `low`.2456 The detail level of the file to be sent to the model. Use `auto` to let the system select the detail level; for GPT-5.6 and later models, `auto` uses high-quality rendering, which may increase input token usage. Use `low` for lower-cost rendering, or `high` to render the file at higher quality. Defaults to `auto`.

2457

2458 - `const ResponseInputFileDetailAuto ResponseInputFileDetail = "auto"`

2357 2459

2358 - `const ResponseInputFileDetailLow ResponseInputFileDetail = "low"`2460 - `const ResponseInputFileDetailLow ResponseInputFileDetail = "low"`

2359 2461

2375 2477

2376 The name of the file to be sent to the model.2478 The name of the file to be sent to the model.

2377 2479

2480 - `PromptCacheBreakpoint ResponseInputFilePromptCacheBreakpoint`

2481

2482 Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.

2483

2484 - `Mode Explicit`

2485

2486 The breakpoint mode. Always `explicit`.

2487

2488 - `const ExplicitExplicit Explicit = "explicit"`

2489

2378 - `Version string`2490 - `Version string`

2379 2491

2380 Optional version of the prompt template.2492 Optional version of the prompt template.

2493 2605

2494 - `const McpMcp Mcp = "mcp"`2606 - `const McpMcp Mcp = "mcp"`

2495 2607

2608 - `AllowedCallers []string`

2609

2610 The tool invocation context(s).

2611

2612 - `const RealtimeSessionCreateResponseToolMcpToolAllowedCallerDirect RealtimeSessionCreateResponseToolMcpToolAllowedCaller = "direct"`

2613

2614 - `const RealtimeSessionCreateResponseToolMcpToolAllowedCallerProgrammatic RealtimeSessionCreateResponseToolMcpToolAllowedCaller = "programmatic"`

2615

2496 - `AllowedTools RealtimeSessionCreateResponseToolMcpToolAllowedToolsUnion`2616 - `AllowedTools RealtimeSessionCreateResponseToolMcpToolAllowedToolsUnion`

2497 2617

2498 List of allowed tool names or a filter object.2618 List of allowed tool names or a filter object.

go/resources/realtime/subresources/client_secrets/index.md 2026-07-07 08:02 UTC to 2026-07-09 20:58 UTC

Client Secrets

Create client secret

Parameters

Returns

Example

Response

Domain Types

Realtime Session Create Response

Realtime Transcription Session Create Response

Realtime Transcription Session Turn Detection